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Identifying influencers from sampled social networks
http://hdl.handle.net/2241/00153720
http://hdl.handle.net/2241/001537204628c329-0da2-490b-9c27-3b13c1b33071
名前 / ファイル | ライセンス | アクション |
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PhyA_507 (279.4 kB)
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Item type | Journal Article(1) | |||||
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公開日 | 2018-11-21 | |||||
タイトル | ||||||
タイトル | Identifying influencers from sampled social networks | |||||
言語 | ||||||
言語 | eng | |||||
資源タイプ | ||||||
資源 | http://purl.org/coar/resource_type/c_6501 | |||||
タイプ | journal article | |||||
著者 |
Tsugawa, Sho
× Tsugawa, Sho× Kimura, Kazuma |
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著者別名 |
津川, 翔
× 津川, 翔 |
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抄録 | ||||||
内容記述タイプ | Abstract | |||||
内容記述 | Identifying influencers who can spread information to many other individuals from a social network is a fundamental research task in the network science research field. Several measures for identifying influencers have been proposed, and the effectiveness of these influence measures has been evaluated for the case where the complete social network structure is known. However, it is difficult in practice to obtain the complete structure of a social network because of missing data, false data, or node/link sampling from the social network. In this paper, we investigate the effects of node sampling from a social network on the effectiveness of influence measures at identifying influencers. Our experimental results show that the negative effect of biased sampling, such as sample edge count, on the identification of influencers is generally small. For social media networks, we can identify influencers whose influence is comparable with that of those identified from the complete social networks by sampling only 10%–30% of the networks. Moreover, our results also suggest the possible benefit of network sampling in the identification of influencers. Our results show that, for some networks, nodes with higher influence can be discovered from sampled social networks than from complete social networks. | |||||
書誌情報 |
Physica. A, Statistical mechanics and its applications 巻 507, p. 294-303, 発行日 2018-10 |
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ISSN | ||||||
収録物識別子タイプ | ISSN | |||||
収録物識別子 | 03784371 | |||||
書誌レコードID | ||||||
収録物識別子タイプ | NCID | |||||
収録物識別子 | AA11252758 | |||||
DOI | ||||||
識別子タイプ | DOI | |||||
関連識別子 | 10.1016/j.physa.2018.05.105 | |||||
権利 | ||||||
権利情報 | © 2017. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/ | |||||
著者版フラグ | ||||||
値 | author | |||||
出版者 | ||||||
出版者 | Elsevier |